Search results

Managers must make numerous strategic decisions in order to initiate and implement a business model innovation (BMI). This paper examines how managers perceive the management team interacts when making BMI decisions. The paper also investigates how group biases and board members’ risk willingness affect this process.

Empirical data were collected through 26 in-depth interviews with German managing directors from 13 companies in four industries (mobility, manufacturing, healthcare and energy) to explore three research questions: (1) What group effects are prevalent in BMI group decision-making? (2) What are the key characteristics of BMI group decisions? And (3) what are the potential relationships between BMI group decision-making and managers' risk willingness? A thematic analysis based on Gioia's guidelines was conducted to identify themes in the comprehensive dataset.

First, the results show four typical group biases in BMI group decisions: Groupthink, social influence, hidden profile and group polarization. Findings show that the hidden profile paradigm and groupthink theory are essential in the context of BMI decisions. Second, we developed a BMI decision matrix, including the following key characteristics of BMI group decision-making managerial cohesion, conflict readiness and information- and emotion-based decision behavior. Third, in contrast to previous literature, we found that individual risk aversion can improve the quality of BMI decisions.

This paper provides managers with an opportunity to become aware of group biases that may impede their strategic BMI decisions. Specifically, it points out that managers should consider the key cognitive constraints due to their interactions when making BMI decisions. This work also highlights the importance of risk-averse decision-makers on boards.

This qualitative study contributes to the literature on decision-making by revealing key cognitive group biases in strategic decision-making. This study also enriches the behavioral science research stream of the BMI literature by attributing a critical influence on the quality of BMI decisions to managers' group interactions. In addition, this article provides new perspectives on managers' risk aversion in strategic decision-making.

This study aims to use regression Least-Square Support Vector Machine (LS-SVM) as a probabilistic model to determine the factor of safety (FS) and probability of failure (PF) of anisotropic soil slopes.

This research uses machine learning (ML) techniques to predict soil slope failure. Due to the lack of analytical solutions for measuring FS and PF, it is more convenient to use surrogate models like probabilistic modeling, which is suitable for performing repetitive calculations to compute the effect of uncertainty on the anisotropic soil slope stability. The study first uses the Limit Equilibrium Method (LEM) based on a probabilistic evaluation over the Latin Hypercube Sampling (LHS) technique for two anisotropic soil slope profiles to assess FS and PF. Then, using one of the supervised methods of ML named LS-SVM, the outcomes (FS and PF) were compared to evaluate the efficiency of the LS-SVM method in predicting the stability of such complex soil slope profiles.

This method increases the computational performance of low-probability analysis significantly. The compared results by FS-PF plots show that the proposed method is valuable for analyzing complex slopes under different probabilistic distributions. Accordingly, to obtain a precise estimate of slope stability, all layers must be included in the probabilistic modeling in the LS-SVM method.

Combining LS-SVM and LEM offers a unique and innovative approach to address the anisotropic behavior of soil slope stability analysis. The initiative part of this paper is to evaluate the stability of an anisotropic soil slope based on one ML method, the Least-Square Support Vector Machine (LS-SVM). The soil slope is defined as complex because there are uncertainties in the slope profile characteristics transformed to LS-SVM. Consequently, several input parameters are effective in finding FS and PF as output parameters.

This study aims to understand how distributed agile teams (DATs), encouraged by globalisation, and recently accelerated by the COVID-19 outbreak, adopt agile practices to achieve project goals by working virtually.

This study developed a multiple-case study involving four companies undergoing several changes, especially during the COVID-19 pandemic. The authors collected data mainly through in-depth, face-to-face interviews with seven key informants. Moreover, this study operates data triangulation by referring to secondary data sources and developing a grounded theory data analysis.

The findings highlight three main categories associated with the DAT functioning, namely, “DATs’ implementation issues”, “elements supporting DATs’ implementation” and “outcomes of DATs’ implementation”, that show DATs’ primary triggers, critical aspects and supportive actions for team functioning.

This paper produced valuable theoretical knowledge of DATs’ dynamics within a socio-technical approach that distinguishes soft and hard variables supporting DAT implementation. Moreover, the evidence provides useful suggestions for managers about creating an objective-oriented virtual work environment based on DATs’ self-organisation, digitally shared leadership and occasional on-site socialisation.

This paper provides new and interesting insights that bring to evidence the main variables related to DATs’ adoption and dynamics, showing supporting activities that enhanced their operativity. It provides a valuable descriptive framework for academics and practitioners to understand DATs’ functioning better and take action to improve their implementation.

The purpose of this study is to explore the contributions of peace and security to the self-development of educators in Syria. It focuses on understanding how these elements impact the equitable distribution of benefits, treatment, facilities and resources. The study aims to uncover the intricate relationship between a secure, peaceful educational environment and the personal and professional growth of educators, thereby shedding light on how these factors synergistically enhance the educational landscape in Syria.

This study employs the Partial Least Squares Structural Equation Modelling (PLS-SEM) method for data analysis. Data were gathered through an online survey distributed to 472 Syrian educators from 14 provinces. The questionnaire, provided in Arabic, consisted of sections on demographics, peace and security, religion and cultural values, core values for self-development and government intervention. The data were analysed using IBM SPSS for descriptive analysis and PLS-SEM for causal effect analysis, allowing for the modelling of latent variables and handling non-normality in small to medium-sized samples.

The study found a positive correlation between peace and security, government intervention and self-development among Syrian educators. However, government intervention was identified as a poor moderator due to the unfavourable connection between past government actions and current expectations. The findings challenge the government to be proactive in addressing issues and concerns related to fair treatment and creating a harmonious academic environment. Educators seek equality in support and assistance across various academic activities for their self-development.

The study’s primary limitation is the use of convenience sampling, as the researchers faced difficulties in disseminating the questionnaires due to being non-local. This might affect the generalizability of the findings. Future research could employ a more randomized sampling method and expand the scope to include more diverse educational settings. The implications of this study are significant for policymaking, suggesting that targeted government interventions are necessary to foster a supportive and secure environment for educators.

The study underscores the need for more effective government policies that prioritize peace and security in educational settings. These interventions are crucial for the well-being and development of educators, ultimately improving educational quality in Syria. Practical recommendations include continuous support for educators through professional development programmes and equitable distribution of resources. By fostering a supportive environment, educators can better contribute to the educational sector and broader societal development.

By highlighting the critical role of peace and security in educators' self-development, the study contributes to broader social stability and cohesion. It advocates for policies that address the diverse needs and challenges faced by educators in Syria, ensuring they are well-supported in their roles. Enhancing educators' well-being and effectiveness can lead to improved educational outcomes, benefiting students and contributing to the nation’s long-term social and economic development.

This study provides a unique contribution by focusing on the nexus of peace, security and self-development among educators in Syria, an area previously underexplored. The findings offer valuable insights into the specific challenges and needs of educators in a conflict-affected region. The research emphasizes the importance of a peaceful and secure educational environment for the professional growth of educators, offering a foundation for future studies and policy discussions aimed at enhancing the educational landscape in Syria.

The main objective of this paper is to analyze how leadership unity (LU) within universities affects the innovativeness of faculty, with a focus on the potential moderating role of strategic sensitivity (SS).

The conceptual model of this research shows that SS and LU of the university impact the faculty's innovativeness. Meantime, the moderating effect of SS is assessed. A 49-item questionnaire was administered to 350 respondents who were managers and faculties of the university. The hierarchical regression technique was used for analyzing data and testing hypotheses.

The findings support both a curvilinear relationship based on a concave upward pattern and a linear relationship between LU in the university and the innovativeness of faculty. In addition, the university's SS positively influences the faculty's innovativeness. SS negatively moderates the curvilinear relationship between LU and faculty's innovativeness, i.e. the U-shaped effect exists only when the level of SS is high.

The results of this study shed new light on the relationships between LU and SS with innovativeness in the higher education landscape. It underlines the importance of SS as a moderator in the relationship between LU and innovativeness. This study was conducted in a developing country under sanctions with an Eastern culture, Iran. Thus, it is recommended that the conceptual framework of this study be tested in different countries with cultural diversity to generalize its findings.

Administrators of universities need to recognize that creating unity and cohesion among managers of various levels of the university is crucial. They should also be aware that responses to external changes can lead to new opportunities for the university. Embracing transformation within the organizational strategies of the university will have a significant influence on competition, politics, and internal operations.

This research contributes to the academic discussions on the importance of LU and SS and also the moderation effect of SS in driving and promoting innovativeness in among faculties by providing empirical evidence. The results present valuable insights for scholars, practitioners and policymakers seeking to understand innovativeness among faculties in the higher education setting.

Social media played an irreplaceable role in young people’s online social life and information consumption during the COVID-19 pandemic. This research focuses on the impact of excessive information on social media about COVID-19 vaccines on Generation Z's (Gen Z) associated psychological states and long-term vaccine advocacy.

The research conducted structural equation modeling analysis with online survey data from 409 Gen Z citizens in the UK.

The findings suggest that excessive information increased Gen Z social media users' ambivalence and conspiracy beliefs around COVID-19 vaccines, which, in turn, reduced their long-term vaccine advocacy in terms of vaccine acceptance, vaccination intention and vaccine promotion. Importantly, Gen Z’s confidence in government and in the healthcare systems during COVID-19 was effective in helping them overcome the detrimental effects of conspiracy beliefs and ambivalence about long-term vaccine advocacy, respectively.

This research reveals the “dark side” of social media use in the post-pandemic period and highlights the significant roles played by social institutions in mitigating the detrimental effects of Gen Z’s support in social decisions. Beyond the context of COVID-19, this research has important implications for facilitating the civic engagement of Gen Z and boosting their confidence in social institutions in terms of social cohesion.

Our aim was to elucidate how leaders’ behaviors may impact innovation and organizational learning in a fast-changing, human-centric and sustainability responsive AI-driven Industry 5.0 environment.

An unsystematic narrative review of relevant literature was conducted focusing on the influence of leadership behaviors on innovation and learning in Industry 5.0 environment.

We found that leadership behaviors that align with Industry 5.0 demands and values must emphasize collaboration, empathy, and continuous learning. The translation of leaders’ actions into desired outcomes requires a psychologically safe work environment, ensuing team cohesion, empowering team members, promoting a learning culture, engendering trust, and vision and goal alignment.

Being aware of leadership qualities required in Industry 5.0 environment, characterized by machine–human collaboration, sustainable innovations, and continuous learning, enables organizations to focus their recruitment efforts on leaders’ characteristics that align with this environment. It also helps them design suitable leaders’ training and development programs. This study requires further expansion and empirical testing to validate the proposed model.

There is a plethora of studies on leadership in various contexts; however, there is very little research on the type of leadership that maybe effective in the fast changing and AI-driven Industry 5.0 environment. The findings of this paper shed light on such a leadership.

The purpose of this paper is to propose a new combined finite-discrete element method (FDEM) to analyze the mechanical properties, failure behavior and slope stability of soil rock mixtures (SRM), in which the rocks within the SRM model have shape randomness, size randomness and spatial distribution randomness.

Based on the modeling method of heterogeneous rocks, the SRM numerical model can be built and by adjusting the boundary between soil and rock, an SRM numerical model with any rock content can be obtained. The reliability and robustness of the new modeling method can be verified by uniaxial compression simulation. In addition, this paper investigates the effects of rock topology, rock content, slope height and slope inclination on the stability of SRM slopes.

Investigations of the influences of rock content, slope height and slope inclination of SRM slopes showed that the slope height had little effect on the failure mode. The influences of rock content and slope inclination on the slope failure mode were significant. With increasing rock content and slope dip angle, SRM slopes gradually transitioned from a single shear failure mode to a multi-shear fracture failure mode, and shear fractures showed irregular and bifurcated characteristics in which the cut-off values of rock content and slope inclination were 20% and 80°, respectively.

This paper proposed a new modeling method for SRMs based on FDEM, with rocks having random shapes, sizes and spatial distributions.

This study examines whether common directors are guilty of contagion of corporate frauds from the customer side and, if so, how contagion occurs. Moreover, it explores a way to mitigate it, which is the increased digital orientation of firms.

Secondary data analysis is applied in this paper. We extract supply chain relations from the China Stock Market and Account Research (CSMAR) database as well as corporate fraud data from the same database and the official website of the China Securities Regulatory Commission (CSRC). Digital orientations are estimated through text analysis. Poisson regression is conducted to examine the moderating effect of common directors and the moderated moderating effect of the firms’ digital orientations.

By analysing the 2,096 downstream relations from 2000 to 2021 in China, the study reveals that corporate frauds are contagious through supply chains, while only customers’ misconduct can contagion to upstream firms. The presence of common directors strengthens such supply chain contagion. Additionally, the digital orientation can mitigate the positive moderating effect of common directors on supply chain contagion.

This study highlights the importance of understanding supply chain contagion through corporate fraud by (1) emphasising the existence of the contagion effects of corporate frauds; (2) understanding the potential channel in the process of contagion; (3) considering how digital orientation can mitigate this contagion and (4) recognising that the effect of contagion comes only from the downstream, not from the upstream.